ASAP: Attention-Shift-Aware Pruning for Efficient LVLM Inference
ASAP: Attention-Shift-Aware Pruning for Efficient LVLM Inference explores ASAP is a novel pruning method that enhances the efficiency of Large Vision-Language Models by addressing attention shifts and reducing token redundancy.. Commercial viability score: 7/10 in Efficient Inference.
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